title: Useful screening tools for preventing foot problems of diabetics in rural areas: a cross-sectional study.
abstract: BACKGROUND
  Preventing diabetic foot problems (DFP) and their associated consequences is a critical in rural regions. The objective is to present an association of non-invasive DFP assessment tools and physiological indicators for early detection among rural cases of diabetes in Taiwan.
  
  
  METHODS
  Secondary data analysis of 387 participants previously diagnosed with type 2 diabetes was used. The Michigan Neuropathy Screening Instrument (MNSI), Ankle Brachial Index (ABI), optimal scaling combination (OSC) of MNSI, and age were used to examine peripheral neurovascular function. The King's College classification (KC) and Texas risk classification (TRC) were used to understand diabetic foot complications.
  
  
  RESULTS
  The findings indicated that MNSI was negatively correlated with ABI, but positively with diabetes duration, age, KC, TRC, fasting blood glucose, low density of lipoprotein cholesterol, body mass index and waist circumference. The area under the receiver operating characteristic curves for assessing the risk of ABI based on OSC was larger than for MNSI, KC, and TRC.
  
  
  CONCLUSIONS
  It is shown that using OSC, MNSI, and ABI as community screening tools is useful in detecting early neurovasculopathy. In addition, where an ABI machine is unavailable, primary healthcare providers that perform MNSI or OSC may be cost-effective. The study was approved by the institutional review board of the ethical committee (No 98-2224-B).
authors.affiliation: Graduate Institute of Nursing, Chang Gung University of Science and Technology, Chiayi Campus, Taiwan. meiyen@gw.cgust.edu.tw.
authors.forename: Chia-Hao
authors.initials: CH
authors.lastname: Chang
authors.forename: Yun-Shing
authors.initials: YS
authors.lastname: Peng
authors.forename: Chang-Cheng
authors.initials: CC
authors.lastname: Chang
authors.forename: Mei-Yen
authors.initials: MY
authors.lastname: Chen
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D055109:Ankle Brachial Index; D019540:Area Under Curve; D015415:Biomarkers; D001786:Blood Glucose / Q000378:metabolism; D015992:Body Mass Index; D002784:Cholesterol / Q000097:blood; D003430:Cross-Sectional Studies; D003924:Diabetes Mellitus, Type 2 / Q000150:complications*; D017719:Diabetic Foot / Q000175:diagnosis* / Q000517:prevention & control; D042241:Early Diagnosis; D005260:Female; D006801:Humans; D008074:Lipoproteins / Q000097:blood; D008297:Male; D008403:Mass Screening / Q000379:methods*; D008875:Middle Aged; D012372:ROC Curve; D012424:Rural Population; D013624:Taiwan
chemical_list: D015415:Biomarkers; D001786:Blood Glucose; D008074:Lipoproteins; C030104:lipoprotein cholesterol; D002784:Cholesterol